Spin up clusters and build quickly in a managed Apache Spark environment. Clusters are set up, configured and fine-tuned to ensure high reliability and performance.

Autoscale and auto-terminate

Reduce resources and costs associated with scaling clusters manually by autoscaling up and down with your needs. Auto-terminate your inactive clusters to save resources.

Collaborative workspace

An interactive workspace enables data engineers, data scientists and business users to collaborate and comment on shared projects as a team.

Optimised for deep learning

Easily build, train and deploy AI models at scale using GPU-enabled clusters. Use runtime for machine learning that comes preinstalled and preconfigured with deep learning frameworks and libraries such as TensorFlow, Keras and XGBoost.

Azure Databricks supports languages like Python, Scala, R and SQL so you can use your existing skills to start building. Target any amount of data or any project size using a comprehensive set of analytics technologies including SQL, Streaming, MLlib and GraphX.

What can you do with Azure Databricks?

Modern data warehouse

Easily bring together all your data at any scale and get insights through analytical dashboards, operational reports and advanced analytics for all your users with a modern data warehouse.

Advanced analytics on big data

Transform your data into actionable insights using best-in-class machine learning tools. This architecture allows you to combine any data at any scale and to build and deploy custom machine learning models.

Real-time analytics

Get insights from streaming data with ease. Capture data continuously from any streaming source or logs from website clickstreams and process it in near-real time.